How is it different from simple test coverage tools?

Unlike tools that focus on vanity metrics like coverage percentage, this skill prioritizes outcomes like how many bugs actually reach production and the time taken to recover from failures.

What are the primary metrics tracked by this skill?

It focuses on DORA metrics (Deployment Frequency, Lead Time, CFR, MTTR) and quality outcomes like Bug Escape Rate, MTTD, and Test Effectiveness.

Can I use this for CI/CD pipelines?

Yes, it provides specific configurations for setting up blocking quality gates at the commit, pull request, and release stages.

How does this skill use AI agents?

It coordinates specialized agents like the qe-quality-analyzer and qe-quality-gate to automatically monitor trends, calculate density, and enforce build policies.

Quality Metrics & Dashboards

Name: Quality Metrics & Dashboards
Author: natea

bynatea

Analíticas y Monitorización

Measures software quality and delivery performance using actionable DORA metrics, quality gates, and automated trend analysis.

Acerca de

The Quality Metrics skill empowers Claude to establish data-driven quality frameworks by implementing industry-standard measurement patterns like DORA and bug escape rates. It moves beyond vanity metrics to focus on high-impact outcomes like Mean Time to Detect (MTTD) and Change Failure Rate, enabling agents to automatically configure quality gates, generate Grafana dashboards, and perform long-term trend analysis. This skill is essential for engineering teams looking to justify quality investments and maintain high standards across the software development lifecycle through automated observability.

Características Principales

Outcome-focused measurement including Bug Escape Rate and Test Effectiveness
Automated dashboard design templates for observability platforms
0 GitHub stars
Actionable quality gate configuration with blocking and warning thresholds
Automated DORA metrics tracking including Deployment Frequency and MTTR
AI-driven trend analysis and predictive quality reporting over 90-day cycles

Casos de Uso

Establishing automated quality gates to block defective code in CI/CD pipelines
Analyzing long-term defect density and bug escape trends to optimize testing strategies
Creating executive-level quality dashboards that track real outcomes over vanity metrics

Acerca de

Características Principales

Outcome-focused measurement including Bug Escape Rate and Test Effectiveness
Automated dashboard design templates for observability platforms
0 GitHub stars
Actionable quality gate configuration with blocking and warning thresholds
Automated DORA metrics tracking including Deployment Frequency and MTTR
AI-driven trend analysis and predictive quality reporting over 90-day cycles

Casos de Uso

Establishing automated quality gates to block defective code in CI/CD pipelines
Analyzing long-term defect density and bug escape trends to optimize testing strategies
Creating executive-level quality dashboards that track real outcomes over vanity metrics